Merge to Spotfire Integration
AI-first ETL from Merge into Spotfire. Governed entities, incremental sync, typed landing tables.
How Datrise loads Merge into Spotfire
Datrise syncs Merge's linked accounts, employees, candidates, contacts, invoices, and sync statuses into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.
Ideal for interactive analytical visualization and data science.
Endpoints
Merge: Unified API across HR, CRM, and accounting tools.
Spotfire: Visual analytics platform for interactive dashboards and data science workflows.
How Merge entities map to Spotfire
| Merge entity | Spotfire object | Notes |
|---|---|---|
| linked accounts | merge_linked_accounts | id PK · custom fields → flattened columns for visualizations |
| employees | merge_employees | id PK · linked to merge_linked_accounts |
| candidates | merge_candidates | id PK · linked to merge_linked_accounts |
| contacts | merge_contacts | id PK · linked to merge_linked_accounts |
FAQ
How does Datrise handle Merge's custom fields in Spotfire?
Flexible values are stored as flattened columns for visualizations, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spotfire types.
How does the Merge to Spotfire sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.
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